Development of the human nervous system involves complex interactions between fundamental cellular processes and requires a multitude of genes, many of which remain to be associated with human disease. We applied whole exome sequencing to 128 mostly consanguineous families with neurogenetic disorders that often included brain malformations. Rare variant analyses for both single nucleotide variant (SNV) and copy number variant (CNV) alleles allowed for identification of 45 novel variants in 43 known disease genes, 41 candidate genes, and CNVs in 10 families, with an overall potential molecular cause identified in >85% of families studied. Among the candidate genes identified, we found PRUNE, VARS, and DHX37 in multiple families, and homozygous loss of function variants in AGBL2, SLC18A2, SMARCA1, UBQLN1, and CPLX1. Neuroimaging and in silico analysis of functional and expression proximity between candidate and known disease genes allowed for further understanding of genetic networks underlying specific types of brain malformations.
De novo germline variants in several components of the SWI/SNF-like BAF complex can cause Coffin-Siris syndrome (CSS), Nicolaides-Baraitser syndrome (NCBRS), and nonsyndromic intellectual disability. We screened 63 patients with a clinical diagnosis of CSS for these genes (ARID1A, ARID1B, SMARCA2, SMARCA4, SMARCB1, and SMARCE1) and identified pathogenic variants in 45 (71%) patients. We found a high proportion of variants in ARID1B (68%). All four pathogenic variants in ARID1A appeared to be mosaic. By using all variants from the Exome Variant Server as test data, we were able to classify variants in ARID1A, ARID1B, and SMARCB1 reliably as being pathogenic or nonpathogenic. For SMARCA2, SMARCA4, and SMARCE1 several variants in the EVS remained unclassified, underlining the importance of parental testing. We have entered all variant and clinical information in LOVD-powered databases to facilitate further genotype-phenotype correlations, as these will become increasingly important because of the uptake of targeted and untargeted next generation sequencing in diagnostics. The emerging phenotype-genotype correlation is that SMARCB1 patients have the most marked physical phenotype and severe cognitive and growth delay. The variability in phenotype seems most marked in ARID1A and ARID1B patients. Distal limbs anomalies are most marked in ARID1A patients and least in SMARCB1 patients. Numbers are small however, and larger series are needed to confirm this correlation.
CLP1 is a RNA kinase involved in tRNA splicing. Recently, CLP1 kinase-dead mice were shown to display a neuromuscular disorder with loss of motor neurons and muscle paralysis. Human genome analyses now identified a CLP1 homozygous missense mutation (p.R140H) in five unrelated families, leading to a loss of CLP1 interaction with the tRNA splicing endonuclease (TSEN) complex, largely reduced pre-tRNA cleavage activity, and accumulation of linear tRNA introns. The affected individuals develop severe motor-sensory defects, cortical dysgenesis and microcephaly. Mice carrying kinase-dead CLP1 also displayed microcephaly and reduced cortical brain volume due to the enhanced cell death of neuronal progenitors that is associated with reduced numbers of cortical neurons. Our data elucidate a novel neurological syndrome defined by CLP1 mutations that impair tRNA splicing. Reduction of a founder mutation to homozygosity illustrates the importance of rare variations in disease and supports the clan genomics hypothesis.
Background Primary immunodeficiency diseases (PIDDs) are clinically and genetically heterogeneous disorders thus far associated with mutations in more than 300 genes. The clinical phenotypes derived from distinct genotypes may overlap. Genetic etiology can be a prognostic indicator of disease severity and can influence treatment decisions. Objective To investigate the ability of whole-exome screening methods to detect disease-causing variants in individuals with PIDDs. Methods Individuals with PIDDs from 278 families from 22 countries were investigated using whole-exome sequencing (WES). Computational CNV prediction pipelines and an exome-tiling chromosomal microarray were also applied to identify intragenic copy number variants (CNVs). Analytic approaches initially focused on 475 known or candidate PIDD genes, but were non-exclusive and were further tailored based upon clinical data, family history and immunophenotyping. Results A likely molecular diagnosis was achieved in 110 (40%) unrelated probands. Clinical diagnosis was revised in about half (60/110) and management was directly altered in nearly a quarter (26/110) of families based on the molecular findings. Twelve PIDD-causing CNVs were detected, including seven smaller than 30 Kb that would not have been detected with conventional diagnostic CNV arrays. Conclusion This high-throughput genomic approach enabled detection of disease-related variants in unexpected genes, permitted detection of low-grade constitutional, somatic and revertant mosaicism, and provided evidence of a mutational burden in mixed PIDD immunophenotypes.
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